Jonathan Schmidt

4.8k citations
39 papers · 3.4k · 1 hit paper · h-index 18

Impact in

    • Machine Learning in Materials Science
    • X-ray Diffraction in Crystallography
    • Electronic and Structural Properties of Oxides
    • 2D Materials and Applications

Papers in

Jonathan Schmidt

35 papers receiving 3.4k citations

Jonathan Schmidt's Hit Papers

Recent advances and applications of machine learning in solid-state materials science 2019 · 1.8k citations
1.8k0+2+4Years since publication50010001.5k

Peers

Jonathan Schmidt
Comparison fields: 5 of 160
  • Materials Chemistry 2.1k
  • Structural Biology 31
  • Catalysis 149
  • Metals and Alloys 55
  • Computational Theory and Mathematics 344
Replace Kamal Choudhary with:
Kamal Choudhary United States
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Jonathan Schmidt relative to Kamal Choudhary United States Kamal Choudhary's profile →
Citations per field
00.5×1.7×
Kamal Choudhary · 1×
Citations per year

Countries citing papers authored by Jonathan Schmidt

Since Specialization
Citations

This map shows the geographic impact of Jonathan Schmidt's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jonathan Schmidt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Schmidt more than expected).

Fields of papers citing papers by Jonathan Schmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Schmidt. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jonathan Schmidt. The network helps show where Jonathan Schmidt may publish in the future.

Co-authors

The 25 scholars most cited alongside Jonathan Schmidt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonathan Schmidt Line = papers co-authored together Jonathan Schmidt links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Recent advances and applications of machine learning in solid-state materials science
Hit paper breakdown →
20191826
2 2017277
3 2020263
4 2012185
5 2008171
6 202196
7 201978
8 202366
9 202455
10 200839
11 202234
12 201833
13 202232
14 202124
15 202124
16 200822
17 200722
18 201920
19 202316
20 202516

About Jonathan Schmidt

Jonathan Schmidt is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering, Inorganic Chemistry and Condensed Matter Physics, having authored 39 papers that have together received 3.4k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (21 papers), X-ray Diffraction in Crystallography (8 papers), Spectroscopy and Quantum Chemical Studies (5 papers), Computational Drug Discovery Methods (4 papers), Catalysis and Oxidation Reactions (4 papers), Inorganic Chemistry and Materials (4 papers), Advanced Chemical Physics Studies (3 papers) and Perovskite Materials and Applications (3 papers). The work is most often cited by research in Materials Chemistry (2.1k citations), Structural Biology (31 citations), Catalysis (149 citations), Metals and Alloys (55 citations) and Computational Theory and Mathematics (344 citations). Jonathan Schmidt has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Miguel A. L. Marques, Silvana Botti, Mário R. G. Marques, Pedro Borlido, John C. Tully, Priya V. Parandekar, Liming Chen, Jingming Shi, Ahmad W. Huran and Fabien Tran. Their work appears in journals such as npj Computational Materials, The Journal of Chemical Physics, Physical review. B., Machine Learning Science and Technology and Physical Review A.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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